The design parameters are automatically computed based on internal
quality determination and the sampling ratios desired. Based on the
design parameters, the windowed-sinc filter is generated. For music use,
the resampler for 44.1 to 48 kHz and vice versa is generated at a higher
quality than for arbitrary frequency conversion.

The audio resamplers provide increased quality, as well as speed
to achieve that quality. But resamplers can introduce small amounts
of passband ripple and aliasing harmonic noise, and they can cause some high
frequency loss in the transition band, so avoid using them unnecessarily.

Best Practices for Sampling and Resampling

This section describes some best practices to help you avoid problems with sampling rates.

Choose the sampling rate to fit the device

In general, it is best to choose the sampling rate to fit the device,
typically 44.1 kHz or 48 kHz. Use of a sample rate greater than
48 kHz will typically result in decreased quality because a resampler must be
used to play back the file.

Use simple resampling ratios (fixed versus interpolated polyphases)

The resampler operates in one of the following modes:

Fixed polyphase mode. The filter coefficients for each polyphase are precomputed.

Interpolated polyphase mode. The filter coefficients for each polyphase must
be interpolated from the nearest two precomputed polyphases.

The resampler is fastest in fixed polyphase mode, when the ratio of input
rate over output rate L/M (taking out the greatest common divisor)
has M less than 256. For example, for 44,100 to 48,000 conversion, L = 147,
M = 160.

In fixed polyphase mode, the sampling rate is locked and does not change. In interpolated
polyphase mode, the sampling rate is approximate. When playing on a 48-kHz device the sampling rate
drift is generally one sample over a few hours. This is not usually a concern because the
approximation error is much less than the frequency error contributed by internal quartz
oscillators, thermal drift, or jitter (typically tens of ppm).

Choose simple-ratio sampling rates such as 24 kHz (1:2) and 32 kHz (2:3) when playing back
on a 48-kHz device, even though other sampling
rates and ratios may be permitted through AudioTrack.

Use upsampling rather than downsampling when changing sample rates

Sampling rates can be changed on the fly. The granularity of
such change is based on the internal buffering (typically a few hundred
samples), not on a sample-by-sample basis. This can be used for effects.

Do not dynamically change sampling rates when
downsampling. When changing sample rates after an audio track is
created, differences of around 5 to 10 percent from the original rate may
trigger a filter recomputation when downsampling (to properly suppress
aliasing). This can consume computing resources and may cause an audible click
if the filter is replaced in real time.

Limit downsampling to no more than 6:1

Downsampling is typically triggered by hardware device requirements. When the
Sample Rate converter is used for downsampling,
try to limit the downsampling ratio to no more than 6:1 for good aliasing
suppression (for example, no greater downsample than 48,000 to 8,000). The filter
lengths adjust to match the downsampling ratio, but you sacrifice more
transition bandwidth at higher downsampling ratios to avoid excessively
increasing the filter length. There are no similar aliasing concerns for
upsampling. Note that some parts of the audio pipeline
may prevent downsampling greater than 2:1.

If you are concerned about latency, do not resample

Resampling prevents the track from being placed in the FastMixer
path, which means that significantly higher latency occurs due to the additional,
larger buffer in the ordinary Mixer path. Furthermore,
there is an implicit delay from the filter length of the resampler,
though this is typically on the order of one millisecond or less,
which is not as large as the additional buffering for the ordinary Mixer path
(typically 20 milliseconds).

Using floating-point audio

Using floating-point numbers to represent audio data can significantly enhance audio
quality in high-performance audio applications. Floating point offers the following
advantages:

Wider dynamic range.

Consistent accuracy across the dynamic range.

More headroom to avoid clipping during intermediate calculations and transients.

While floating-point can enhance audio quality, it does present certain disadvantages:

Formerly, floating-point was notorious for being unavailable or slow. This is
still true for low-end and embedded processors. But processors on modern
mobile devices now have hardware floating-point with performance that is
similar (or in some cases even faster) than integer. Modern CPUs also support
SIMD
(Single instruction, multiple data), which can improve performance further.

Best Practices for Floating-Point Audio

The following best practices help you avoid problems with floating-point calculations:

Use double precision floating-point for infrequent calculations,
such as computing filter coefficients.

Pay attention to the order of operations.

Declare explicit variables for intermediate values.

Use parentheses liberally.

If you get a NaN or infinity result, use binary search to discover
where it was introduced.

For floating-point audio, the audio format encoding
AudioFormat.ENCODING_PCM_FLOAT is used similarly to
ENCODING_PCM_16_BIT or ENCODING_PCM_8_BIT for specifying
AudioTrack data
formats. The corresponding overloaded method AudioTrack.write()
takes in a float array to deliver data.